Introduction

Testing over 1000 materials per year for a wide range of physical properties, DatapointLabs is a center of excellence providing global support to industries engaged in new product development and R&D.

The compary meets the material property needs of CAE/FEA analysts, with a specialized product line, TestPaks®, which allow CAE analysts to easily order material testing for the calibration of over 100 different material models. ...more

CAE partners

The TestPaks Alliance Program was formed in 1998 to create a collaborative environment between DatapointLabs and CAE companies to provide material model calibration services. Working with more than 20 CAE vendors and supporting over 29 codes we have created of a specialized catalog of TestPaks for CAE.

With TestPaks, at the end of the testing, you will receive not just test results, but analysis-ready input decks. Our staff is familiar with your needs and, jointly with your software technical support, will provide complete solutions to your material modeling needs....more

Driven by quality

We rely on our ISO 17025 quality system to ensure the precision and traceability of our instruments. Our personnel are trained to conform to the high standards of this system. Participation in proficiency testing programs verifies the consistency of our data. A2LA, the national lab accreditation body certifies that we meet the requirements of the ISO/IEC 17025-1999, and operate in accordance with ISO 9001 or 9002....more

Physically accurate simulation is a requirement for initiatives such as late-stage prototyping, additive manufacturing, and digital twinning. Simulations use mathematical models to replicate physical reality. Verification and validation
(V&V) is an important step for high-fidelity simulation. While verification is a way to check the accuracy of these
models, factors such as simulation settings, element type, mesh size, choice of material model, material parameter conversion process, quality and suitability of material property data used can have a large impact on simulation quality. Validation presents a means to check simulation accuracy against a physical experiment.
These validations are a valuable tool to measure solver accuracy prior to use in product development. Confidence is gained that the simulation replicates real-life physical
behavior.

The modeling of material behavior for injection molded plastics is a vital step for good simulation results. We detail the types of material data needed by various injection-molding simulation programs, factors that can affect simulation quality including test techniques and process variables such as moisture content. The case of fiber filled plastics is covered along with the extension to structural analysis applications.

Physically accurate simulation is a requirement for initiatives such as late-stage prototyping, additive manufacturing and digital twinning. The use of mid-stage validation has been shown to be a valuable tool to measure solver accuracy prior to use in simulation. Factors such as simulation settings, element type, mesh size, choice of material model, the material model parameter conversion process, quality and suitability of material property data used can all be evaluated. These validations do not use real-life parts, but instead use carefully designed standardized geometries in a controlled physical test that probes the accuracy of the simulation. With this a priori knowledge, it is possible to make meaningful design decisions. Confidence is gained that the simulation replicates real-life physical behavior. We present three case studies using different solvers and materials, which illustrate the broad applicability of this technique.

Performing simulations that can approximate the material behavior of ductile plastics is daunting. Factors such as nonlinear elasticity, inclusion of volumetric and deviatoric behavior, finding and correctly applying the proper material data to create failure criteria are only a few hurdles. A variety of material models exist, each with numerous settings and varied parameter conversion methods. Combined, these cause a great deal of uncertainty for the FEA user. In previous papers, we delved into material models for both LS-DYNA (MAT089, MAT024, and MAT187) and ABAQUS (*ELASTIC, *PLASTIC) using mid-stage validation as a technique to probe solver accuracy. In this presentation, we summarize our findings on the benefits of this combined approach as a general tool to test and tune simulations for greater reliability.

Plastics exhibit non-linear viscoelastic behavior followed by a combination of deviatoric and volumetric plastic deformation until failure. Capturing these phenomena correctly in simulation presents a challenge because of limitations in commonly used material models. We follow an approach where we outline the general behavioral phenomena, then prescribe material models for handling different phases of plastics deformation. Edge cases will then be covered to complete the picture. Topics to be addressed include: Using elasto-plasticity; When to use hyperelasticity; Brittle polymers – filled plastics; Failure modes to consider; Criteria for survival; Choosing materials; Spatial non-isotropy from injection molding; Importance of residual stress; Visco-elastic and creep effects; Strain-rate effects for drop test and crash simulations; Fitting material data to FEA material models; The use of mid-stage validation as a tool to confirm the quality of simulation before use in real-life applications.

Hyperelastic material models are complex in nature requiring stress-strain properties in uniaxial, biaxial and shear modes. The data need to be self-consistent in order to fit the commonly used material models. Choosing models and fitting this data to these equations adds additional uncertainty to the process. We present a validation mechanism where, using of a standard validation experiment one can compare results from a simulation and a physical test to obtain a quantified measure of simulation quality. Validated models can be used with greater confidence in the design of real-life components.

Finite element analysis of plastics contains assumptions and uncertainties that can affect simulation accuracy. It is useful to quantify these effects prior to using simulation for real-life applications. A mid-stage validation uses a controlled physical test on a standardized part to compare results from simulation to physical experiment. These validations do not use real-life parts but carefully designed geometries that probe the accuracy of the simulation; the geometries themselves can be tested with boundary conditions that can be simulated correctly. In one study, a quasi-static three-point bending experiment of a standardized parallel ribbed plate is performed and simulated, using Abaqus. A comparison of the strain fields resulting from the complex stress state on the face of the ribs obtained by digital image correlation (DIC) vs. simulation is used to quantify the simulation's fidelity. In a second study, a dynamic dart impact experiment is validated using LS-Dyna probing the multi-axial deformation of a polypropylene until failure.

Quantifying simulation accuracy before running crash simulations could be a helpful confidence building measure. This study continues our development of a mechanism to validate material models for plastics used in modeling high-speed impact. Focusing on models for isotropic materials that include options for rate dependency and failure, we explore other models commonly used for ductile plastics including MAT089 and MAT187.

With the advent of 3D printing and additive manufacturing, manufacturing designs previously thought difficult to produce can now be generated quickly and efficiently and without tooling. In the aerospace industry, weight is often tied directly to cost and is thus of great importance to any engineering design. Traditionally, the design process often involves much iteration between the designer and the analyst, where the designer submits a design to the analyst, and then the analyst completes his or her analysis and sends recommendations back to the designer. The process is repeated until a valid design meets the analysis criteria. The design is then handed to the manufacturing team which then may have additional constraints or concerns and iterations can continue. Additive manufacturing coupled with topology optimization allows the design and analysis loops and manufacturing iterations to be reduced significantly or even eliminated. The critical step is to ensure that the part will perform as simulated.

This book is intended to be a companion to the NAFEMS book, "An Introduction to the Use of Material Models in FE". It informs Finite Element Analysis users of the manner and methodologies by which materials are tested in order to calibrate material models currently implemented in various FEA programs. While the authors seek first to satisfy the basic material models outlined in the companion book, they make important extensions to FEA used in currently active areas including explicit simulation.

Simulations contain assumptions and uncertainties that a designer must evaluate to obtain a measure of accuracy. The assumptions of the product design can be differentiated from the ones for the solver and material model through the use of a mid-stage validation. An open loop validation uses a controlled test on a standardized part to compare results from a simulation to the physical experiment. From the validation, confidence in the material model and solver is gained. In this study, the material properties of a polypropylene are tested to characterize for an *ELASTIC *PLASTIC model in ABAQUS. A validation of a quasi-static three-point bending experiment of a parallel ribbed plate is then performed and simulated. A comparison of the strain fields resulting from the complex stress state on the face of the ribs obtained by digital image correlation (DIC) vs. simulation is used to quantify the simulation's fidelity.

Thermoplastic materials are one of the largest categories of materials to be injection molded. Moisture-sensitive materials can lead to issues in the molding process. Simulation of the injection molding process requires sophisticated and exact material properties to be measured. This presentation discusses the testing required to characterize a thermoplastic material for use in SIGMASOFT, as well as the effects of moisture on viscosity measurement of a moisture-sensitive material. Consequences of basing designs on wet or dry materials are covered. Implementation of material data into the software to produce a successful injection molding simulation simulation is described.

With the growing interest in 3D printing, there is a desire to accurately simulate the behavior of components made by this process. The layer by layer print process appears to create a morphology that is different from that from conventional manufacturing processes. This can have dramatic impact on the material properties, which in turn, can affect how the material is modeled in simulation. In the first stage of our work, we seek to test an additively manufactured material for mechanical properties and validate its use in ANSYS simulation using the Cornell Bike Crank model.

There is interest in quantifying the accuracy of different material models being used in LS-DYNA today for the modeling of plastics. In our study, we characterize two ductile, yet different materials, ABS and polypropylene for rate dependent tensile properties and use the data to develop material parameters for the material models commonly used for plastics: MAT_024 and its variants, MAT_089 and MAT_187. We then perform a falling dart impact test which produces a complex multi-axial stress state and simulate this experiment using LS-DYNA. For each material model we are able to compare simulation to actual experiment thereby obtaining a measure of fidelity of the simulation to reality. In this way, we can assess the benefits of using a particular material model for plastics simulation.

Finite-element analysis and injection-molding simulation are two technologies that are seeing widespread use today in the design of plastic components. Limitations exist in our ability to mathematically describe the complexity of polymer behavior to these software packages. Material models commonly used in finite-element analysis were not designed for plastics, making it difficult to correctly describe non-linear behavior and plasticity of these complex materials. Time-based viscoelastic phenomena further complicate analysis. Dealing with fiber fillers brings yet another layer of complexity. It is vital to the plastics engineer to comprehend these gaps in order to make good design decisions. Approaches to understanding and dealing with these challenges, including practical strategies for everyday use, will be discussed.

Thermoplastic materials are one of the largest categories of materials to be injection molded. Simulation of the injection molding process requires sophisticated and exact material properties to be measured. This presentation will discuss the testing required to characterize a material for use in SIGMASOFT, as well as the significance of material model parameters. Differences in testing methodology for amorphous and semi-crystalline polymers will be covered, along with step-by-step implementation into the software to produce a successful injection molding simulation simulation.

It has long been desired to quantify the accuracy of simulation results. Through developments in digital image correlation (DIC) techniques, it is now possible to quantify the deviation between simulation and real life experimentation. In this paper, three-dimension DIC measurements of deformed parts are compared to deformed surfaces predicted in simulation. Using DIC, it is possible to import deformed surface elements from simulation and map the magnitude of deviation from the measurements of the actual deformed shape.

LS-DYNA software contains a wealth of material models that allow for the simulation of transient phenomena. The Matereality® CAE Modeler is a generalized pre-processor software used to convert material property data into material parameters for different material models used in CAE. In a continuation of previously presented work, we discuss the extension of the CAE Modeler software to commonly used material models beyond MAT_024. Software enhancements include advanced point picking to perform extrapolations beyond the tested data, as well as the ability to fine-tune the material models while scrutinizing the trends shown in the underlying raw data. Advanced modeling features include the ability to tune the rate dependency as well as the initial response. Additional material models that are quite complex and difficult to calibrate are supported, including those for hyperelastic and viscoelastic behavior. As before, the written material cards are directly readable into the LS-DYNA software, but now they can also be stored and catalogued in a material card library for later reuse.

Plastics exhibit non-linear viscoelastic behavior followed by a combination of deviatoric and volumetric plastic deformation until failure. Capturing these phenomena correctly in simulation presents a challenge because of the inadequacy of currently used material models. We follow an approach where we outline the general behavioral phenomena, then prescribe material models for handling different phases of plastics deformation. Edge cases will then be covered to complete the picture. Topics to be addressed include: Using elasto-plasticity; When to use hyperelasticity; Brittle polymers – filled plastics; Failure modes to consider; Criteria for survival; Choosing materials; Spatial non-isotropy from injection molding; Importance of residual stress; Visco-elastic and creep effects; Strain-rate effects for drop test and crash simulations; Fitting material data to FEA material models.

Material specifications define properties for incoming materials to meet required criteria. We present software that manages creation of material specifications, input of properties and material composition; and provides a way to evaluate qualification per specification. While it is designed for OEM/Tier n environments, it is also applicable for materials suppliers.

Plastics appeared as design materials of choice about 30 years ago. They brought with them huge design challenges because their multi-variable, non-linear nature was not well understood by engineers trained to work in a linear elastic world. We outline a 20 year journey accompanying our customers in their efforts to understand and simulate these remarkable materials to produce the highly reliable plastic products of today. We discuss challenges related to processes such as injection molding vs. blow-molding; coping with filled plastics; the difficulties of modeling polymers for crash applications. We include our latest findings related to volumetric yield in polymers and its relationship to failure. We describe the material database technology that was created to store this kind of multi-variable data and the analytical tools created to help the CAE engineer understand and use plastics material data.

The use of CAE in design decision-making has created a need for proven simulation accuracy. The two areas where simulation touches the ground are with material data and experimental verification and validation (V&V). Precise, well designed and quantitative experiments are key to ensure that the simulation initiates with correct material behavior. Similar validation experiments are needed to verify simulation and manage the risk associated with this predictive technology.

As part of Cornell University's mechanical engineering curriculum and study of classical beam theory, an aluminium beam is deformed to a specific load. Theoretical strains are calculated at certain points along the beam using beam theory, and then verified by using strain gauges placed at these points on the beam. This experiment is then extended to simulation of the same test setup in simulation software, where strains are analyzed at the same points. Discrepancies between the simulation, theory, and strain gauge results have often plagued the test, especially when incorporating more complex beam design. Through use of digital image correlation (DIC) it is possible to pinpoint some of the problem areas in the beam analysis and provide a better understanding of the localized strains that occur at any point in the deformed beam. The use of DIC provides a full field validation of simulation data, rather than a single spot check that strain gauges can provide. This validation technique helps to eliminate error that is associated with strain gauge placement and the possibility of missing strain hot spots that can arise when analyzing complex deformations or geometries.

There is interest in quantifying the differences between simulation and real life experimentation. This kind of work establishes a baseline for more complex simulations bringing a notion of traceability to the practice of CAE. We present the use of digital image correlation as a way to capture strain fields from component testing and compare these to simulation. Factors that are important in ensuring fidelity between simulation and experiment will be discussed.

The development of material parameters for FEA is heavily reliant on precision material data that captures the stress-strain relationship with fidelity. While conventional methods involving UTMs and extensometers are quite adequate for obtaining such data on a number of materials, there are important cases where they have been known to be inadequate. The testing of composites to obtain directional properties remains a complex task because of the difficulty related to measuring these properties in different orientations. Digital Image Correlation (DIC) methods are able to capture the stress-strain relationship all the way to failure. In this paper, we combine DIC and conventional methods to measure directional properties of composites. We exploit the unique capability of DIC to retroactively place virtual strain gauges in areas of critical interest in the test specimen. Utilising an Iosipescu fixture, we measure shear properties of structured composites in a variety of orientations to compute the parameters of an orthotropic linear elastic material model. Model consistency is checked by validation using Abaqus.

Today, CAE is integrated with modern automotive product development. This creates new challenges for departments that support new product development. In the materials arena, the testing is elevated to much higher levels of sophistication and precision to accommodate the complex material models used in CAE. It is no longer simple matter to convert raw data into material model parameters. We present an end-to-end strategy that gives automakers a well managed pathway to transforming to simulation-based design. We operate a quick-turnaround expert material testing lab to support high-end CAE and product development. We provide a data management software designed specifically to capture and display material data of any complexity. The software can transform raw material data into material parameter files for most commonly used simulations. The CAE Modeler software is of adequate sophistication to fit equations to data, visualize material models along with raw data, and output material cards. Examples for high strain-rate crash material modeling will be presented.

SAMP-1 is a complex material model designed to capture non-Mises yield and localization behavior in plastics. To perform well, it is highly dependent on accurate post-yield material data. A number of assumptions and approximations are currently used to translate measured stress-strain data into the material parameters related to these inputs. In this paper, we look at the use of direct localized strain measurements using digital image correlation (DIC) as a way to more directly extract the required data needed for SAMP-1.

DatapointLabs' TestPaks (material testing + model calibration + Abaqus input decks) for rate-dependent, hyperelastic, viscoelastic, NVH, and the use of Abaqus CAE Modeler to transform raw data into material cards will be presented. A representative from Idiada will present a case study explaining the use of DatapointLabs’ material data and TestPaks for simulation.

The testing of materials for use in crash and safety simulations and the conversion of test data into material models is a process that is not well standardized in the industry. Consequently, CAE users face uncertainty and risk in this process that can have a negative impact on simulation quality. In this workshop, we present approaches currently used in the US for the gathering of high quality test data plus the acclaimed Matereality CAE Modeler software that is used to transform high strain-rate data into crash material cards.

We present a methodology for DIGIMAT users to perform the DIGIMAT MX reverse engineering process to obtain material parameter inputs for crash, elasto-plastic, creep and visco-elasticity. The injection-molding process used involves a standardized plaque geometry with fully developed flow, with test specimens taken from a specific plaque location. A standardized testing procedure is applied and the resulting DIGIMAT MX inputs are handled in a streamlined data stream, which saves time and improves the reliability of the reverse engineering process. The DIGIMAT MX reverse engineering itself can be performed as a service in collaboration with e-Xstream. This gives the user a speedy and tightly controlled process for performing complex finite element analysis with filled plastics

Ultra-high molecular weight polyethylene (UHMWPE) is used extensively in orthopedic applications within the human body. Components made from these materials are subject to complex loading over extended periods of time. Modeling of components used in such applications depends heavily on having material data under in-vivo conditions. We present mechanical and visco-elastic properties measured in saline at 37C. Comparisons to conventionally measured properties at room temperature are made.

The limitations of modeling materials for simulation are discussed, including lack of clarity in material model requirements, gaps between the material data and the model to which it will be fitted, issues in obtaining pertinent properties, difficulties in parameter conversion (fitting), and preparation of input files for the software being used. Means to address these limitations are presented, including understanding the model completely, measuring the correct data with precision on the right material, selecting the best model for the data and ensuring the best fit of the model to the data, validating the model against a simple experiment, and following best practices to create an error-free input file.

Many material models are available for crash simulation. However, common models are not designed for plastics. We present best practices developed for adapting common models to plastics, as well as best testing protocols to generate clean, accurate rate-dependent data. In addition, we present a streamlined process to convert raw data to LS-DYNA material cards, and harmonized material datasets that allow the same raw data to be used for other crash and rate-dependent analysis software.

Material testing for simulation is about understanding how to best describe a material’s behavior as input for the CAE code. Such testing requires expertise and experience beyond testing performed in a typical test laboratory; while the test instruments may be the same, the knowledge of CAE and experience with diverse materials is increasingly important. FEA software such as ANSYS is being increasingly used for non-linear simulations. We discuss how DatapointLabs' uncommon material expertise helps you avoid problems when the data is being generated these applications.

Over the past couple of decades, standard test methods and material models have existed for rubber-like materials. These materials were classified under the category of Hyperelastic materials. Well established physical test methods and computational procedures exist for the characterization of the material behavior in tension, compression, shear volumetric response, tear strength etc. However, effective modeling of the fracture behavior of hyperelastic materials using finite element techniques is very challenging. In this paper, we make an attempt to demonstrate the use of such standard test methods and the applicability of such test data for performing finite element analyses of complex nonlinear problems using Abaqus. Our goal is to demonstrate the effective use of standard physical test data to model multi-axial loading situations and fracture of hyperelastic materials through tear tests and indentation test simulations.

High strain rate material modelling of polymers for use in crash and drop testing has been plagued by a number of problems. These include poor quality and noisy data, material models unsuited to polymer behaviour and unclear material model calibration guidelines. The modelling of polymers is thus a risky proposition with a highly variable success rate. In previous work, we tackled each of the above problems individually. In this paper, we summarize and then proceed to present a material modelling strategy that can be applied for a wide variety of polymers.

We seek to lay down a framework to help us understand the different behavioral classes of foams. Following a methodology that we previously applied to plastics, we will then attempt to propose the right LS-DYNA material models that best capture these behaviours. Guidelines for model selection will be presented as well as best practices for characterization. Limitations of existing material models will be discussed.

Abaqus’ Non-linear NVH capability permits the capture of material behavior of rubber seals and bushings, plastic parts and foam inserts which have a significant influence on the simulation. In this presentation, we discuss material calibration procedures for this application.

If you want a crash simulation involving plastics to yield useful results, it is important to model the material behavior appropriately. The high strain rates have a significant effect on the properties, and failure can be ductile or brittle in nature, depending on a number of factors.

We present a perspective on material modeling as applied to mold analysis requirements. Melt-solid transitions and the case for a unified material model are discussed, along with prediction of post-filling material behavior and shrinkage, and the impact of viscous heating on flow behavior and material degradation.

Many LS-DYNA models are used for plastics crash simulation. However, common models are not designed for plastics. We present best practices developed for adapting common models to plastics, as well as best testing protocols to generate clean, accurate rate-dependent data.

A considerable amount of CAE today is devoted to the simulation of non-metallic materials, many of which exhibit non-linear behavior. However, most material models to date are still based on metals theory. This places severe restrictions on the proper description of their behavior in CAE. In this paper, we describe non-linear elastic behavior and its interrelationship with plastic behavior in plastics. Special attention is given to the differentiation between visco-elastic (recoverable) strain and plastic (non-recoverable) strain. The goal of this work is to have a material model for plastics that can describe both loading and unloading behavior accurately and provide an accurate measure of damage accumulation during complex loading operations.

The volume of plastics that are subjected to impact simulation has grown rapidly. In a previous paper, we discussed why different material models are needed to describe the highly varied behavior exhibited by these materials. In this paper, we cover the subject in more detail, exploring in depth, the nuances of commonly used LS-DYNA material models for plastics, covering important exceptions and criteria related to their use.

The volume of plastics that are subjected to impact simulation has grown rapidly. In a
previous paper, we discussed why different material models are needed to describe the
highly varied behavior exhibited by these materials. In this paper, we cover the subject
in more detail, exploring in depth, the nuances of commonly used LS-DYNA material
models for plastics, covering important exceptions and criteria related to their use.

High strain-rate properties have many applications in the simulation of automotive crash and product drop testing.
These properties are difficult to measure. These difficulties result from inaccuracies in extensometry at high strain
rates due to extensometer slippage and background noise due to the sudden increase in stress at the start of the
test. To eliminate these inaccuracies we use an inferential technique that correlates strain to extension at low
strain rates and show that this can be extended to measure strain at higher strain rates

Assurance of quality in raw materials, control over production, and a basic understanding of criteria for performance all require a sure and complete
knowledge of analytical methods for plastics. The present volume organizes the vast world of plastics analysis into a relatively compact form. A plastics engineer will find familiar territory in such subjects as
rheometry, differential scanning calorimetry, and measurement of thermal properties. Polymer physicists and chemists will be at home with spectroscopic analyses, liquid chromatography, and nuclear magnetic resonance. All these topics and many more are covered in twelve chapters written by an impressive array of experts drawn from industry and academia.

There has been a long standing need for a book that describes the
process of injection molding using the insights developed from twenty years of computer aided engineering (CAE). The authors, all veterans of injection molding CAE, have filled this need with their book. "Successful
Injection Molding" is a lot more than a book about injection molding CAE. It is clear at this stage that CAE is a tool, which, if well handled, can provide excellent results. That being said, a successful implementer of CAE for injection molding must have a range of insights into the diverse
idiosyncrasies of this enormously complex manufacturing process. The book is successful in clearly addressing these issues.

Hyperelastic models are used extensively in the finite element analysis of rubber and elastomers. These models need to be able to describe elastomeric behavior at large deformations and under different modes of deformation. In order to accomplish this daunting task, material models have been presented that can mathematically describe this behavior [1]. There are several in common use today, notably, the Mooney-Rivlin, Ogden and Arruda Boyce. Each of these has advantages that we will discuss in this article. Further, we will examine the applicability of a particular material model for a given modeling situation.

We discuss material properties in injection molding simulations, including the definition of property requirements, identification of evaluation parameters, and the role of material properties at each stage of the injection molding process, from mold filling through cooling, post-filling and shrinkage/warpage considerations.

With the recent changes in the crashworthiness requirements for US automobiles for improved safety, design engineers are being challenged to design interior trim systems comprised of polymeric materials to meet these new impact requirements. Impact analysis programs are being used increasingly by designers to gain an insight into the final part performance during the design stage. Material models play a crucial role in these design simulations by representing the response of the material to an applied stimulus. In this work, we seek to develop novel test methods to generate high speed stress-strain properties of plastics, which can be used as input to structural analysis programs...

This book presents a concise and easily readable introduction to polymer behavior for design and production engineers. It seeks to explain the behavior of plastics and rubber using a materials science framework, by relating observed phenomena to changes in morphological and molecular structure. This presents a powerful way for engineers to grasp the underlying factors that make polymers the complex materials that they are. The reader is encouraged to step away from using linear-elastic metals concepts when designing with plastics. The pitfalls of such
simplifications are pointed out and guidelines are presented to aid the designer in adopting a non-linear approach.

Two approaches to polymer processing rheology are discernible; by theoreticians. who are concerned with a fundamental description of what would be happening if certain idealized criteria are met; and by practitioners, who are concerned with the results of what is actually happening.” In his newly revised book, Mr. Cogswell skillfully treads the middle ground between these camps, providing an interesting, informative guide to rheology for the design engineer.

This book presents a valuable resource for engineers and designers seeking to apply structural analysis and other advanced methods to the design of plastic parts. The reader learns what to expect for the mechanical properties of polymers and develops a grasp of how plastics respond to various applied stress conditions. The book introduces mechanical tests and polymer transitions, moving onward into chapters on elastic behavior, creep and stress relaxation, dynamic mechanical properties, stress- strain behavior and strength, It also covers abrasion, fatigue, friction and stress cracking. Additionally, the effects of fillers and fibers on these properties are considered.

This book, edited by the Wisconsin based team of Osswald, Turng and Gramman, represents a compilation of work by several well known authors and brings together a body of knowledge that will be appreciated by injection molding professionals and students of plastics processing.

The primary purpose of this book is to describe the application of modern engineering analysis techniques to the design of components fabricated from thermoplastic materials. The book, the first of its kind to address the unique behavioral characteristics of thermoplastics and their impact on finite element analysis (FEA), points out the need for plastics designers to move on to nonlinear analysis in order to truly simulate the behavior of plastic parts. According to the authors, the easy availability of high speed computing and efficient analysis codes means that it is no longer necessary nor cost-effective to restrict oneself to simple linear analyses.

Finite-element analysis and injection-molding simulation are two technologies that are seeing widespread use today in the design of plastic components. Limitations exist in our ability to mathematically describe the complexity of polymer behavior to these software packages. Material models commonly used in finite-element analysis were not designed for plastics, making it difficult to correctly describe non-linear behavior and plasticity of these complex materials. Time-based viscoelastic phenomena further complicate analysis. Dealing with fiber fillers brings yet another layer of complexity. It is vital to the plastics engineer to comprehend these gaps in order to make good design decisions. Approaches to understanding and dealing with these challenges, including practical strategies for everyday use, will be discussed.
...click to view

High strain-rate properties have many applications in the simulation of automotive crash and product drop testing.
These properties are difficult to measure. These difficulties result from inaccuracies in extensometry at high strain
rates due to extensometer slippage and background noise due to the sudden increase in stress at the start of the
test. To eliminate these inaccuracies we use an inferential technique that correlates strain to extension at low
strain rates and show that this can be extended to measure strain at higher strain rates ...click to view

Thermoplastic materials are one of the largest categories of materials to be injection molded. Simulation of the injection molding process requires sophisticated and exact material properties to be measured. This presentation will discuss the testing required to characterize a material for use in SIGMASOFT, as well as the significance of material model parameters. Differences in testing methodology for amorphous and semi-crystalline polymers will be covered, along with step-by-step implementation into the software to produce a successful injection molding simulation simulation.
...click to view

High strain rate material modelling of polymers for use in crash and drop testing has been plagued by a number of problems. These include poor quality and noisy data, material models unsuited to polymer behaviour and unclear material model calibration guidelines. The modelling of polymers is thus a risky proposition with a highly variable success rate. In previous work, we tackled each of the above problems individually. In this paper, we summarize and then proceed to present a material modelling strategy that can be applied for a wide variety of polymers. ...click to view

The volume of plastics that are subjected to impact simulation has grown rapidly. In a
previous paper, we discussed why different material models are needed to describe the
highly varied behavior exhibited by these materials. In this paper, we cover the subject
in more detail, exploring in depth, the nuances of commonly used LS-DYNA material
models for plastics, covering important exceptions and criteria related to their use. ...click to view

With the recent changes in the crashworthiness requirements for US automobiles for improved safety, design engineers are being challenged to design interior trim systems comprised of polymeric materials to meet these new impact requirements. Impact analysis programs are being used increasingly by designers to gain an insight into the final part performance during the design stage. Material models play a crucial role in these design simulations by representing the response of the material to an applied stimulus. In this work, we seek to develop novel test methods to generate high speed stress-strain properties of plastics, which can be used as input to structural analysis programs...
...click to view

We discuss material properties in injection molding simulations, including the definition of property requirements, identification of evaluation parameters, and the role of material properties at each stage of the injection molding process, from mold filling through cooling, post-filling and shrinkage/warpage considerations. ...click to view

We discuss developments in viscosity modeling. New models are not generalized, but are designed to predict expected trends for polymers and incorporate both Newtonian and shear-thinning behavior.
...click to view

Hyperelastic models are used extensively in the finite element analysis of rubber and elastomers. These models need to be able to describe elastomeric behavior at large deformations and under different modes of deformation. In order to accomplish this daunting task, material models have been presented that can mathematically describe this behavior [1]. There are several in common use today, notably, the Mooney-Rivlin, Ogden and Arruda Boyce. Each of these has advantages that we will discuss in this article. Further, we will examine the applicability of a particular material model for a given modeling situation.
...click to view

The volume of plastics that are subjected to impact simulation has grown rapidly. In a previous paper, we discussed why different material models are needed to describe the highly varied behavior exhibited by these materials. In this paper, we cover the subject in more detail, exploring in depth, the nuances of commonly used LS-DYNA material models for plastics, covering important exceptions and criteria related to their use. ...click to view

A considerable amount of CAE today is devoted to the simulation of non-metallic materials, many of which exhibit non-linear behavior. However, most material models to date are still based on metals theory. This places severe restrictions on the proper description of their behavior in CAE. In this paper, we describe non-linear elastic behavior and its interrelationship with plastic behavior in plastics. Special attention is given to the differentiation between visco-elastic (recoverable) strain and plastic (non-recoverable) strain. The goal of this work is to have a material model for plastics that can describe both loading and unloading behavior accurately and provide an accurate measure of damage accumulation during complex loading operations.
...click to view

Many LS-DYNA models are used for plastics crash simulation. However, common models are not designed for plastics. We present best practices developed for adapting common models to plastics, as well as best testing protocols to generate clean, accurate rate-dependent data.
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We present a perspective on material modeling as applied to mold analysis requirements. Melt-solid transitions and the case for a unified material model are discussed, along with prediction of post-filling material behavior and shrinkage, and the impact of viscous heating on flow behavior and material degradation.
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If you want a crash simulation involving plastics to yield useful results, it is important to model the material behavior appropriately. The high strain rates have a significant effect on the properties, and failure can be ductile or brittle in nature, depending on a number of factors.
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Abaqus’ Non-linear NVH capability permits the capture of material behavior of rubber seals and bushings, plastic parts and foam inserts which have a significant influence on the simulation. In this presentation, we discuss material calibration procedures for this application.
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We seek to lay down a framework to help us understand the different behavioral classes of foams. Following a methodology that we previously applied to plastics, we will then attempt to propose the right LS-DYNA material models that best capture these behaviours. Guidelines for model selection will be presented as well as best practices for characterization. Limitations of existing material models will be discussed.
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Over the past couple of decades, standard test methods and material models have existed for rubber-like materials. These materials were classified under the category of Hyperelastic materials. Well established physical test methods and computational procedures exist for the characterization of the material behavior in tension, compression, shear volumetric response, tear strength etc. However, effective modeling of the fracture behavior of hyperelastic materials using finite element techniques is very challenging. In this paper, we make an attempt to demonstrate the use of such standard test methods and the applicability of such test data for performing finite element analyses of complex nonlinear problems using Abaqus. Our goal is to demonstrate the effective use of standard physical test data to model multi-axial loading situations and fracture of hyperelastic materials through tear tests and indentation test simulations.
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Material testing for simulation is about understanding how to best describe a material’s behavior as input for the CAE code. Such testing requires expertise and experience beyond testing performed in a typical test laboratory; while the test instruments may be the same, the knowledge of CAE and experience with diverse materials is increasingly important. FEA software such as ANSYS is being increasingly used for non-linear simulations. We discuss how DatapointLabs' uncommon material expertise helps you avoid problems when the data is being generated these applications.
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Many material models are available for crash simulation. However, common models are not designed for plastics. We present best practices developed for adapting common models to plastics, as well as best testing protocols to generate clean, accurate rate-dependent data. In addition, we present a streamlined process to convert raw data to LS-DYNA material cards, and harmonized material datasets that allow the same raw data to be used for other crash and rate-dependent analysis software.
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The limitations of modeling materials for simulation are discussed, including lack of clarity in material model requirements, gaps between the material data and the model to which it will be fitted, issues in obtaining pertinent properties, difficulties in parameter conversion (fitting), and preparation of input files for the software being used. Means to address these limitations are presented, including understanding the model completely, measuring the correct data with precision on the right material, selecting the best model for the data and ensuring the best fit of the model to the data, validating the model against a simple experiment, and following best practices to create an error-free input file.
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Ultra-high molecular weight polyethylene (UHMWPE) is used extensively in orthopedic applications within the human body. Components made from these materials are subject to complex loading over extended periods of time. Modeling of components used in such applications depends heavily on having material data under in-vivo conditions. We present mechanical and visco-elastic properties measured in saline at 37C. Comparisons to conventionally measured properties at room temperature are made.
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We present a methodology for DIGIMAT users to perform the DIGIMAT MX reverse engineering process to obtain material parameter inputs for crash, elasto-plastic, creep and visco-elasticity. The injection-molding process used involves a standardized plaque geometry with fully developed flow, with test specimens taken from a specific plaque location. A standardized testing procedure is applied and the resulting DIGIMAT MX inputs are handled in a streamlined data stream, which saves time and improves the reliability of the reverse engineering process. The DIGIMAT MX reverse engineering itself can be performed as a service in collaboration with e-Xstream. This gives the user a speedy and tightly controlled process for performing complex finite element analysis with filled plastics
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The testing of materials for use in crash and safety simulations and the conversion of test data into material models is a process that is not well standardized in the industry. Consequently, CAE users face uncertainty and risk in this process that can have a negative impact on simulation quality. In this workshop, we present approaches currently used in the US for the gathering of high quality test data plus the acclaimed Matereality CAE Modeler software that is used to transform high strain-rate data into crash material cards.
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DatapointLabs' TestPaks (material testing + model calibration + Abaqus input decks) for rate-dependent, hyperelastic, viscoelastic, NVH, and the use of Abaqus CAE Modeler to transform raw data into material cards will be presented. A representative from Idiada will present a case study explaining the use of DatapointLabs’ material data and TestPaks for simulation.
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SAMP-1 is a complex material model designed to capture non-Mises yield and localization behavior in plastics. To perform well, it is highly dependent on accurate post-yield material data. A number of assumptions and approximations are currently used to translate measured stress-strain data into the material parameters related to these inputs. In this paper, we look at the use of direct localized strain measurements using digital image correlation (DIC) as a way to more directly extract the required data needed for SAMP-1.
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Today, CAE is integrated with modern automotive product development. This creates new challenges for departments that support new product development. In the materials arena, the testing is elevated to much higher levels of sophistication and precision to accommodate the complex material models used in CAE. It is no longer simple matter to convert raw data into material model parameters. We present an end-to-end strategy that gives automakers a well managed pathway to transforming to simulation-based design. We operate a quick-turnaround expert material testing lab to support high-end CAE and product development. We provide a data management software designed specifically to capture and display material data of any complexity. The software can transform raw material data into material parameter files for most commonly used simulations. The CAE Modeler software is of adequate sophistication to fit equations to data, visualize material models along with raw data, and output material cards. Examples for high strain-rate crash material modeling will be presented.
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The development of material parameters for FEA is heavily reliant on precision material data that captures the stress-strain relationship with fidelity. While conventional methods involving UTMs and extensometers are quite adequate for obtaining such data on a number of materials, there are important cases where they have been known to be inadequate. The testing of composites to obtain directional properties remains a complex task because of the difficulty related to measuring these properties in different orientations. Digital Image Correlation (DIC) methods are able to capture the stress-strain relationship all the way to failure. In this paper, we combine DIC and conventional methods to measure directional properties of composites. We exploit the unique capability of DIC to retroactively place virtual strain gauges in areas of critical interest in the test specimen. Utilising an Iosipescu fixture, we measure shear properties of structured composites in a variety of orientations to compute the parameters of an orthotropic linear elastic material model. Model consistency is checked by validation using Abaqus.
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There is interest in quantifying the differences between simulation and real life experimentation. This kind of work establishes a baseline for more complex simulations bringing a notion of traceability to the practice of CAE. We present the use of digital image correlation as a way to capture strain fields from component testing and compare these to simulation. Factors that are important in ensuring fidelity between simulation and experiment will be discussed.
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As part of Cornell University's mechanical engineering curriculum and study of classical beam theory, an aluminium beam is deformed to a specific load. Theoretical strains are calculated at certain points along the beam using beam theory, and then verified by using strain gauges placed at these points on the beam. This experiment is then extended to simulation of the same test setup in simulation software, where strains are analyzed at the same points. Discrepancies between the simulation, theory, and strain gauge results have often plagued the test, especially when incorporating more complex beam design. Through use of digital image correlation (DIC) it is possible to pinpoint some of the problem areas in the beam analysis and provide a better understanding of the localized strains that occur at any point in the deformed beam. The use of DIC provides a full field validation of simulation data, rather than a single spot check that strain gauges can provide. This validation technique helps to eliminate error that is associated with strain gauge placement and the possibility of missing strain hot spots that can arise when analyzing complex deformations or geometries.
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The use of CAE in design decision-making has created a need for proven simulation accuracy. The two areas where simulation touches the ground are with material data and experimental verification and validation (V&V). Precise, well designed and quantitative experiments are key to ensure that the simulation initiates with correct material behavior. Similar validation experiments are needed to verify simulation and manage the risk associated with this predictive technology.
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Plastics appeared as design materials of choice about 30 years ago. They brought with them huge design challenges because their multi-variable, non-linear nature was not well understood by engineers trained to work in a linear elastic world. We outline a 20 year journey accompanying our customers in their efforts to understand and simulate these remarkable materials to produce the highly reliable plastic products of today. We discuss challenges related to processes such as injection molding vs. blow-molding; coping with filled plastics; the difficulties of modeling polymers for crash applications. We include our latest findings related to volumetric yield in polymers and its relationship to failure. We describe the material database technology that was created to store this kind of multi-variable data and the analytical tools created to help the CAE engineer understand and use plastics material data.
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Material specifications define properties for incoming materials to meet required criteria. We present software that manages creation of material specifications, input of properties and material composition; and provides a way to evaluate qualification per specification. While it is designed for OEM/Tier n environments, it is also applicable for materials suppliers.
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Plastics exhibit non-linear viscoelastic behavior followed by a combination of deviatoric and volumetric plastic deformation until failure. Capturing these phenomena correctly in simulation presents a challenge because of the inadequacy of currently used material models. We follow an approach where we outline the general behavioral phenomena, then prescribe material models for handling different phases of plastics deformation. Edge cases will then be covered to complete the picture. Topics to be addressed include: Using elasto-plasticity; When to use hyperelasticity; Brittle polymers – filled plastics; Failure modes to consider; Criteria for survival; Choosing materials; Spatial non-isotropy from injection molding; Importance of residual stress; Visco-elastic and creep effects; Strain-rate effects for drop test and crash simulations; Fitting material data to FEA material models.
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LS-DYNA software contains a wealth of material models that allow for the simulation of transient phenomena. The Matereality® CAE Modeler is a generalized pre-processor software used to convert material property data into material parameters for different material models used in CAE. In a continuation of previously presented work, we discuss the extension of the CAE Modeler software to commonly used material models beyond MAT_024. Software enhancements include advanced point picking to perform extrapolations beyond the tested data, as well as the ability to fine-tune the material models while scrutinizing the trends shown in the underlying raw data. Advanced modeling features include the ability to tune the rate dependency as well as the initial response. Additional material models that are quite complex and difficult to calibrate are supported, including those for hyperelastic and viscoelastic behavior. As before, the written material cards are directly readable into the LS-DYNA software, but now they can also be stored and catalogued in a material card library for later reuse.
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It has long been desired to quantify the accuracy of simulation results. Through developments in digital image correlation (DIC) techniques, it is now possible to quantify the deviation between simulation and real life experimentation. In this paper, three-dimension DIC measurements of deformed parts are compared to deformed surfaces predicted in simulation. Using DIC, it is possible to import deformed surface elements from simulation and map the magnitude of deviation from the measurements of the actual deformed shape.
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With the growing interest in 3D printing, there is a desire to accurately simulate the behavior of components made by this process. The layer by layer print process appears to create a morphology that is different from that from conventional manufacturing processes. This can have dramatic impact on the material properties, which in turn, can affect how the material is modeled in simulation. In the first stage of our work, we seek to test an additively manufactured material for mechanical properties and validate its use in ANSYS simulation using the Cornell Bike Crank model. ...click to view

There is interest in quantifying the accuracy of different material models being used in LS-DYNA today for the modeling of plastics. In our study, we characterize two ductile, yet different materials, ABS and polypropylene for rate dependent tensile properties and use the data to develop material parameters for the material models commonly used for plastics: MAT_024 and its variants, MAT_089 and MAT_187. We then perform a falling dart impact test which produces a complex multi-axial stress state and simulate this experiment using LS-DYNA. For each material model we are able to compare simulation to actual experiment thereby obtaining a measure of fidelity of the simulation to reality. In this way, we can assess the benefits of using a particular material model for plastics simulation. ...click to view

Thermoplastic materials are one of the largest categories of materials to be injection molded. Moisture-sensitive materials can lead to issues in the molding process. Simulation of the injection molding process requires sophisticated and exact material properties to be measured. This presentation discusses the testing required to characterize a thermoplastic material for use in SIGMASOFT, as well as the effects of moisture on viscosity measurement of a moisture-sensitive material. Consequences of basing designs on wet or dry materials are covered. Implementation of material data into the software to produce a successful injection molding simulation simulation is described. ...click to view

Quantifying simulation accuracy before running crash simulations could be a helpful confidence building measure. This study continues our development of a mechanism to validate material models for plastics used in modeling high-speed impact. Focusing on models for isotropic materials that include options for rate dependency and failure, we explore other models commonly used for ductile plastics including MAT089 and MAT187. ...click to view

Simulations contain assumptions and uncertainties that a designer must evaluate to obtain a measure of accuracy. The assumptions of the product design can be differentiated from the ones for the solver and material model through the use of a mid-stage validation. An open loop validation uses a controlled test on a standardized part to compare results from a simulation to the physical experiment. From the validation, confidence in the material model and solver is gained. In this study, the material properties of a polypropylene are tested to characterize for an *ELASTIC *PLASTIC model in ABAQUS. A validation of a quasi-static three-point bending experiment of a parallel ribbed plate is then performed and simulated. A comparison of the strain fields resulting from the complex stress state on the face of the ribs obtained by digital image correlation (DIC) vs. simulation is used to quantify the simulation's fidelity. ...click to view

With the advent of 3D printing and additive manufacturing, manufacturing designs previously thought difficult to produce can now be generated quickly and efficiently and without tooling. In the aerospace industry, weight is often tied directly to cost and is thus of great importance to any engineering design. Traditionally, the design process often involves much iteration between the designer and the analyst, where the designer submits a design to the analyst, and then the analyst completes his or her analysis and sends recommendations back to the designer. The process is repeated until a valid design meets the analysis criteria. The design is then handed to the manufacturing team which then may have additional constraints or concerns and iterations can continue. Additive manufacturing coupled with topology optimization allows the design and analysis loops and manufacturing iterations to be reduced significantly or even eliminated. The critical step is to ensure that the part will perform as simulated. ...click to view

With the advent of 3D printing and additive manufacturing, manufacturing designs previously thought difficult to produce can now be generated quickly and efficiently and without tooling. In the aerospace industry, weight is often tied directly to cost and is thus of great importance to any engineering design. Traditionally, the design process often involves much iteration between the designer and the analyst, where the designer submits a design to the analyst, and then the analyst completes his or her analysis and sends recommendations back to the designer. The process is repeated until a valid design meets the analysis criteria. The design is then handed to the manufacturing team which then may have additional constraints or concerns and iterations can continue. Additive manufacturing coupled with topology optimization allows the design and analysis loops and manufacturing iterations to be reduced significantly or even eliminated. The critical step is to ensure that the part will perform as simulated. ...click to view

Simulations contain assumptions and uncertainties that a designer must evaluate to obtain a measure of accuracy. The assumptions of the product design can be differentiated from the ones for the solver and material model through the use of a mid-stage validation. An open loop validation uses a controlled test on a standardized part to compare results from a simulation to the physical experiment. From the validation, confidence in the material model and solver is gained. In this study, the material properties of a polypropylene are tested to characterize for an *ELASTIC *PLASTIC model in ABAQUS. A validation of a quasi-static three-point bending experiment of a parallel ribbed plate is then performed and simulated. A comparison of the strain fields resulting from the complex stress state on the face of the ribs obtained by digital image correlation (DIC) vs. simulation is used to quantify the simulation's fidelity. ...click to view

Quantifying simulation accuracy before running crash simulations could be a helpful confidence building measure. This study continues our development of a mechanism to validate material models for plastics used in modeling high-speed impact. Focusing on models for isotropic materials that include options for rate dependency and failure, we explore other models commonly used for ductile plastics including MAT089 and MAT187. ...click to view

Hyperelastic material models are complex in nature requiring stress-strain properties in uniaxial, biaxial and shear modes. The data need to be self-consistent in order to fit the commonly used material models. Choosing models and fitting this data to these equations adds additional uncertainty to the process. We present a validation mechanism where, using of a standard validation experiment one can compare results from a simulation and a physical test to obtain a quantified measure of simulation quality. Validated models can be used with greater confidence in the design of real-life components. ...click to view

Hyperelastic material models are complex in nature requiring stress-strain properties in uniaxial, biaxial and shear modes. The data need to be self-consistent in order to fit the commonly used material models. Choosing models and fitting this data to these equations adds additional uncertainty to the process. We present a validation mechanism where, using of a standard validation experiment one can compare results from a simulation and a physical test to obtain a quantified measure of simulation quality. Validated models can be used with greater confidence in the design of real-life components. ...click to view

Finite element analysis of plastics contains assumptions and uncertainties that can affect simulation accuracy. It is useful to quantify these effects prior to using simulation for real-life applications. A mid-stage validation uses a controlled physical test on a standardized part to compare results from simulation to physical experiment. These validations do not use real-life parts but carefully designed geometries that probe the accuracy of the simulation; the geometries themselves can be tested with boundary conditions that can be simulated correctly. In one study, a quasi-static three-point bending experiment of a standardized parallel ribbed plate is performed and simulated, using Abaqus. A comparison of the strain fields resulting from the complex stress state on the face of the ribs obtained by digital image correlation (DIC) vs. simulation is used to quantify the simulation's fidelity. In a second study, a dynamic dart impact experiment is validated using LS-Dyna probing the multi-axial deformation of a polypropylene until failure. ...click to view

Performing simulations that can approximate the material behavior of ductile plastics is daunting. Factors such as nonlinear elasticity, inclusion of volumetric and deviatoric behavior, finding and correctly applying the proper material data to create failure criteria are only a few hurdles. A variety of material models exist, each with numerous settings and varied parameter conversion methods. Combined, these cause a great deal of uncertainty for the FEA user. In previous papers, we delved into material models for both LS-DYNA (MAT089, MAT024, and MAT187) and ABAQUS (*ELASTIC, *PLASTIC) using mid-stage validation as a technique to probe solver accuracy. In this presentation, we summarize our findings on the benefits of this combined approach as a general tool to test and tune simulations for greater reliability. ...click to view

Physically accurate simulation is a requirement for initiatives such as late-stage prototyping, additive manufacturing and digital twinning. The use of mid-stage validation has been shown to be a valuable tool to measure solver accuracy prior to use in simulation. Factors such as simulation settings, element type, mesh size, choice of material model, the material model parameter conversion process, quality and suitability of material property data used can all be evaluated. These validations do not use real-life parts, but instead use carefully designed standardized geometries in a controlled physical test that probes the accuracy of the simulation. With this a priori knowledge, it is possible to make meaningful design decisions. Confidence is gained that the simulation replicates real-life physical behavior. ...click to view

Physically accurate simulation is a requirement for initiatives such as late-stage prototyping, additive manufacturing and digital twinning. The use of mid-stage validation has been shown to be a valuable tool to measure solver accuracy prior to use in simulation. Factors such as simulation settings, element type, mesh size, choice of material model, the material model parameter conversion process, quality and suitability of material property data used can all be evaluated. These validations do not use real-life parts, but instead use carefully designed standardized geometries in a controlled physical test that probes the accuracy of the simulation. With this a priori knowledge, it is possible to make meaningful design decisions. Confidence is gained that the simulation replicates real-life physical behavior. ...click to view

The modeling of material behavior for injection molded plastics is a vital step for good simulation results. We detail the types of material data needed by various injection-molding simulation programs, factors that can affect simulation quality including test techniques and process variables such as moisture content. The case of fiber filled plastics is covered along with the extension to structural analysis applications. ...click to view